Speech Enhancement Research based on Fractional Fourier transform

Jingfang Wang


As many traditional de-noising methods fail in the intensive noises environment and are unadaptable in various noisy environments, a method of speech enhancement has been advanced based on dynamic Fractional Fourier Transform (FRFT)filtering. The acoustic signals are framed. The renewing methods are put in FRFT optimal disperse degree of noising speech and this method is implemented in detail. By TIMIT criterion voice and Noisex-92, the experimental results show that this algorithm can filter noise from voice availably and improve the performance of automatic speech recognition system significantly. It is proved to be robust under various noisy environments and Signal-to-Noise Ratio (SNR) conditions. This algorithm is of low computational complexity and briefness in realization.




Acoustic signal, Fractional Fourier Transform(FRFT), Speech Enhancemen, de-noising, auto-adaptive processing, Dynamic filtering

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